Convolutional neural networks for extracting a "deep stroma score" from histological images of human cancer
This is Matlab code to train a convolutional neural network for tissue classification in histological images of human cancer. This network can be used to derive a "deep stroma" risk score from such images. Also, this repository contains R code that we used for downstream statistics. The methods are described in our paper "A deep learning based stroma score is an independent prognostic factor in colorectal cancer"
You need the code (provided in this repository) and the images which are available for download here: http://doi.org/10.5281/zenodo.1214456 We used the normalized 100K data set for training, but you can also download the non-normalized 100K data set.
Also, you need to install the "color normalization toolbox" from this link: https://warwick.ac.uk/fac/sci/dcs/research/tia/software/sntoolbox/ You should install it in the sub-folder "subroutines_normalization"
The model is available here: http://doi.org/10.5281/zenodo.1420524